{"id":"https://openalex.org/W3131280860","doi":"https://doi.org/10.1109/globecom42002.2020.9347964","title":"Sparse Channel Reconstruction With Nonconvex Regularizer via DC Programming for Massive MIMO Systems","display_name":"Sparse Channel Reconstruction With Nonconvex Regularizer via DC Programming for Massive MIMO Systems","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3131280860","doi":"https://doi.org/10.1109/globecom42002.2020.9347964","mag":"3131280860"},"language":"en","primary_location":{"id":"doi:10.1109/globecom42002.2020.9347964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9347964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056965264","display_name":"Pengxia Wu","orcid":"https://orcid.org/0000-0002-0826-1614"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]},{"id":"https://openalex.org/I4405260628","display_name":"University of British Columbia, Okanagan Campus","ror":"https://ror.org/04241wz75","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Pengxia Wu","raw_affiliation_strings":["School of Engineering, The University of British Columbia, Kelowna, BC, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering, The University of British Columbia, Kelowna, BC, Canada","institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083661553","display_name":"Hui Ma","orcid":"https://orcid.org/0000-0002-2502-3933"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]},{"id":"https://openalex.org/I4405260628","display_name":"University of British Columbia, Okanagan Campus","ror":"https://ror.org/04241wz75","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hui Ma","raw_affiliation_strings":["School of Engineering, The University of British Columbia, Kelowna, BC, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering, The University of British Columbia, Kelowna, BC, Canada","institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045995606","display_name":"Julian Cheng","orcid":"https://orcid.org/0000-0001-6310-8236"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]},{"id":"https://openalex.org/I4405260628","display_name":"University of British Columbia, Okanagan Campus","ror":"https://ror.org/04241wz75","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Julian Cheng","raw_affiliation_strings":["School of Engineering, The University of British Columbia, Kelowna, BC, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering, The University of British Columbia, Kelowna, BC, Canada","institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056965264"],"corresponding_institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"],"apc_list":null,"apc_paid":null,"fwci":0.5384,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63284803,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5568199157714844},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5484817028045654},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5378010272979736},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5284856557846069},{"id":"https://openalex.org/keywords/coordinate-descent","display_name":"Coordinate descent","score":0.519763171672821},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.48420265316963196},{"id":"https://openalex.org/keywords/semidefinite-programming","display_name":"Semidefinite programming","score":0.4793482720851898},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4739549160003662},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4650142788887024},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4491167962551117},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44684475660324097},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.43987610936164856},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.42569291591644287},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.4239165484905243},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4163901209831238},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3263167440891266},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19716081023216248},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1029076874256134},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.09349146485328674}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5568199157714844},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5484817028045654},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5378010272979736},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5284856557846069},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.519763171672821},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.48420265316963196},{"id":"https://openalex.org/C101901036","wikidata":"https://www.wikidata.org/wiki/Q2269096","display_name":"Semidefinite programming","level":2,"score":0.4793482720851898},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4739549160003662},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4650142788887024},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4491167962551117},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44684475660324097},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.43987610936164856},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.42569291591644287},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.4239165484905243},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4163901209831238},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3263167440891266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19716081023216248},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1029076874256134},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.09349146485328674},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom42002.2020.9347964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9347964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1650958574","https://openalex.org/W1938636034","https://openalex.org/W1980454827","https://openalex.org/W1997834106","https://openalex.org/W2063978378","https://openalex.org/W2075779886","https://openalex.org/W2100556411","https://openalex.org/W2109449402","https://openalex.org/W2120549790","https://openalex.org/W2126607811","https://openalex.org/W2127271355","https://openalex.org/W2128659236","https://openalex.org/W2137628444","https://openalex.org/W2272774410","https://openalex.org/W2289917018","https://openalex.org/W2340859457","https://openalex.org/W2724191955","https://openalex.org/W2738241071","https://openalex.org/W2962959174","https://openalex.org/W4301909677"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2117229703","https://openalex.org/W1983756092","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W3120756218","https://openalex.org/W1982147402","https://openalex.org/W1976208764"],"abstract_inverted_index":{"Sparse":[0],"channel":[1,24,73],"estimation":[2],"for":[3,39,106],"massive":[4],"multiple-input":[5],"multiple-output":[6],"systems":[7],"has":[8],"drawn":[9],"much":[10],"attention":[11],"in":[12,98,143],"recent":[13],"years.":[14],"The":[15],"required":[16],"pilots":[17],"are":[18],"substantially":[19],"reduced":[20],"when":[21],"the":[22,45,53,71,79,90,99,108,113,120,128,138],"sparse":[23,40,72,140],"state":[25],"vectors":[26],"can":[27,87],"be":[28],"reconstructed":[29],"from":[30],"a":[31,49,83],"few":[32],"numbers":[33],"of":[34,115,145],"measurements.":[35],"A":[36,101],"popular":[37],"approach":[38],"reconstruction":[41,74,146],"is":[42,56,75,104,131],"to":[43,60,65],"solve":[44],"least-squares":[46,80],"problem":[47],"with":[48,82],"convex":[50,54,116],"regularization.":[51],"However,":[52],"regularizer":[55],"either":[57],"too":[58],"loose":[59],"force":[61],"sparsity":[62,91],"or":[63],"lead":[64],"biased":[66],"estimation.":[67],"In":[68],"this":[69],"paper,":[70],"solved":[76],"by":[77],"minimizing":[78],"objective":[81],"nonconvex":[84,110],"regularizer,":[85],"which":[86],"exactly":[88],"express":[89],"constraint":[92],"and":[93,119,133,135],"avoid":[94],"introducing":[95],"serious":[96],"bias":[97],"solution.":[100],"novel":[102],"algorithm":[103,130],"proposed":[105,129],"solving":[107],"resulting":[109],"optimization":[111],"via":[112],"difference":[114],"functions":[117],"programming":[118],"gradient":[121],"projection":[122],"descent.":[123],"Simulation":[124],"results":[125],"show":[126],"that":[127],"fast":[132],"accurate,":[134],"it":[136],"outperforms":[137],"existing":[139],"recovery":[141],"algorithms":[142],"terms":[144],"errors.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}